Skip to main content
The Model Context Protocol (MCP) is an open standard for connecting AI applications to external systems. The Atomscale MCP server lets AI tools search, analyze, and manage your metrology data — RHEED, SEM, XPS, ellipsometry, Raman, photoluminescence, and more — directly, without leaving your assistant. Every request is scoped to your Atomscale account: tools act as you, within your organization, and respect the same permissions as the web app.

Endpoint

https://api.atomscale.ai/mcp/
The server speaks streamable-HTTP. The trailing slash is required.

Setup

On first connection your client opens a browser to sign in with your Atomscale account, then caches a token for subsequent requests. Headless clients can authenticate with an API key instead (see Authentication).
claude mcp add --transport http atomscale https://api.atomscale.ai/mcp/
Then run /mcp inside Claude Code to complete sign-in and list the tools.

Authentication

Interactive clients sign in through your browser on first connect. There’s nothing to configure — approve the access request and the client caches its token.

Tools

Your assistant chooses which tools to call. Write tools (marked below) prompt for confirmation in most clients before making changes.
ToolAccessDescription
search_dataReadSearch the data catalogue
fetch_dataReadGet one data item’s metadata by ID
fetch_resultsReadProcessed analysis results or AI summary for a data item
fetch_embeddingsReadSimilarity embeddings for a data item
search_sampleReadSearch physical samples
fetch_sampleReadGet one physical sample by ID
list_notebooksReadList your organization’s analysis notebooks
annotate_dataWriteApply tags and/or attach a note to a data item
add_notebooksWriteCreate an analysis notebook
edit_notebooksWriteCommit a new version of a notebook
upload_dataWriteGet presigned URLs to upload a new file
start_streamWriteStart a timeseries stream
stop_streamWriteFinalize a stream
A ping tool is also available for liveness checks and requires no authentication.